Can Hardware Distortion Correlation be Neglected When Analyzing Uplink SE in Massive MIMO?

This paper analyzes how the distortion created by hardware impairments in a multiple-antenna base station affects the uplink spectral efficiency (SE), with focus on Massive MIMO. The distortion is correlated across the antennas, but has been often approximated as uncorrelated to facilitate (tractable) SE analysis. To determine when this approximation is accurate, basic properties of the distortion correlation are first uncovered. Then, we focus on third-order non-linearities and prove analytically and numerically that the correlation can be neglected in the SE analysis when there are many users. In i.i.d. Rayleigh fading with equal signal-to-noise ratios, this occurs when having five users.Comment: 5 pages, 3 figures, IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 201

Massive MU-MIMO-OFDM Uplink with Hardware Impairments: Modeling and Analysis

We study the impact of hardware impairments at the base station (BS) of an orthogonal frequency-division multiplexing (OFDM)-based massive multiuser (MU) multiple-input multiple-output (MIMO) uplink system. We leverage Bussgang's theorem to develop accurate models for the distortions caused by nonlinear low-noise amplifiers, local oscillators with phase noise, and oversampling finite-resolution analog-to-digital converters. By combining the individual effects of these hardware models, we obtain a composite model for the BS-side distortion caused by nonideal hardware that takes into account its inherent correlation in time, frequency, and across antennas. We use this composite model to analyze the impact of BS-side hardware impairments on the performance of realistic massive MU-MIMO-OFDM uplink systems

Can Hardware Distortion Correlation be Neglected when Analyzing Uplink SE in Massive MIMO

This paper analyzes how the distortion created by hardware impairments in a multiple-antenna base station affects the uplink spectral efficiency (SE), with focus on Massive MIMO. The distortion is correlated across the antennas, but has been often approximated as uncorrelated to facilitate (tractable) SE analysis. To determine when this approximation is accurate, basic properties of the distortion correlation are first uncovered. Then, we focus on third-order non-linearities and prove analytically and numerically that the correlation can be neglected in the SE analysis when there are many users. In i.i. d, Rayleigh fading with equal sianal-to-noise ratios, this occurs when having five users

Linear Precoding with Low-Resolution DACs for Massive MU-MIMO-OFDM Downlink

We consider the downlink of a massive multiuser (MU) multiple-input multiple-output (MIMO) system in which the base station (BS) is equipped with low-resolution digital-to-analog converters (DACs). In contrast to most existing results, we assume that the system operates over a frequency-selective wideband channel and uses orthogonal frequency division multiplexing (OFDM) to simplify equalization at the user equipments (UEs). Furthermore, we consider the practically relevant case of oversampling DACs. We theoretically analyze the uncoded bit error rate (BER) performance with linear precoders (e.g., zero forcing) and quadrature phase-shift keying using Bussgang's theorem. We also develop a lower bound on the information-theoretic sum-rate throughput achievable with Gaussian inputs, which can be evaluated in closed form for the case of 1-bit DACs. For the case of multi-bit DACs, we derive approximate, yet accurate, expressions for the distortion caused by low-precision DACs, which can be used to establish lower bounds on the corresponding sum-rate throughput. Our results demonstrate that, for a massive MU-MIMO-OFDM system with a 128-antenna BS serving 16 UEs, only 3--4 DAC bits are required to achieve an uncoded BER of 10^-4 with a negligible performance loss compared to the infinite-resolution case at the cost of additional out-of-band emissions. Furthermore, our results highlight the importance of taking into account the inherent spatial and temporal correlations caused by low-precision DACs

Distortion-Aware Linear Precoding for Massive MIMO Downlink Systems with Nonlinear Power Amplifiers

We introduce a framework for linear precoder design over a massive multiple-input multiple-output downlink system in the presence of nonlinear power amplifiers (PAs). By studying the spatial characteristics of the distortion, we demonstrate that conventional linear precoding techniques steer nonlinear distortions towards the users. We show that, by taking into account PA nonlinearity, one can design linear precoders that reduce, and in single-user scenarios, even completely remove the distortion transmitted in the direction of the users. This, however, is achieved at the price of a reduced array gain. To address this issue, we present precoder optimization algorithms that simultaneously take into account the effects of array gain, distortion, multiuser interference, and receiver noise. Specifically, we derive an expression for the achievable sum rate and propose an iterative algorithm that attempts to find the precoding matrix which maximizes this expression. Moreover, using a model for PA power consumption, we propose an algorithm that attempts to find the precoding matrix that minimizes the consumed power for a given minimum achievable sum rate. Our numerical results demonstrate that the proposed distortion-aware precoding techniques provide significant improvements in spectral and energy efficiency compared to conventional linear precoders.Comment: 30 pages, 10 figure